skip to main content

SciTech ConnectSciTech Connect

Title: Using the apparent diffusion coefficient to identifying MGMT promoter methylation status early in glioblastoma: importance of analytical method

Accurate knowledge of O{sup 6}-methylguanine methyltransferase (MGMT) gene promoter subtype in patients with glioblastoma (GBM) is important for treatment. However, this test is not always available. Pre-operative diffusion MRI (dMRI) can be used to probe tumour biology using the apparent diffusion coefficient (ADC); however, its ability to act as a surrogate to predict MGMT status has shown mixed results. We investigated whether this was due to variations in the method used to analyse ADC. We undertook a retrospective study of 32 patients with GBM who had MGMT status measured. Matching pre-operative MRI data were used to calculate the ADC within contrast enhancing regions of tumour. The relationship between ADC and MGMT was examined using two published ADC methods. A strong trend between a measure of ‘minimum ADC’ and methylation status was seen. An elevated minimum ADC was more likely in the methylated compared to the unmethylated MGMT group (U = 56, P = 0.0561). In contrast, utilising a two-mixture model histogram approach, a significant reduction in mean measure of the ‘low ADC’ component within the histogram was associated with an MGMT promoter methylation subtype (P < 0.0246). This study shows that within the same patient cohort, the method selected tomore » analyse ADC measures has a significant bearing on the use of that metric as a surrogate marker of MGMT status. Thus for dMRI data to be clinically useful, consistent methods of data analysis need to be established prior to establishing any relationship with genetic or epigenetic profiling.« less
Authors:
 [1] ; ;  [2] ;  [3] ;  [4] ;  [5] ;  [6] ;  [1] ;  [7] ;  [8] ;  [9] ;  [10] ;  [8] ;  [7] ;  [10]
  1. Centre for Clinical Research, University of Queensland, Brisbane, Queensland (Australia)
  2. Brain Cancer Research Unit, Queensland Institute of Medical Research, Brisbane, Queensland (Australia)
  3. Department of Radiation Oncology, Royal Brisbane and Women's Hospital, Brisbane, Queensland (Australia)
  4. Discipline of Clinical Pharmacology, School of Medicine and Public Health, University of Newcastle, Newcastle, New South Wales (Australia)
  5. Department of Neurosurgery, Royal Brisbane and Women's Hospital, Brisbane, Queensland (Australia)
  6. Queensland PET Service, Royal Brisbane and Women's Hospital, Brisbane, Queensland (Australia)
  7. CSIRO Digital Productivity Flagship, CSIRO, Herston, Queensland (Australia)
  8. Centre for Medical Diagnostic Technologies in Queensland, University of Queensland, Brisbane, Queensland (Australia)
  9. Discipline of Medical Imaging, University of Queensland, St Lucia, Queensland (Australia)
  10. (Australia)
Publication Date:
OSTI Identifier:
22402369
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Medical Radiation Sciences (Print); Journal Volume: 62; Journal Issue: 2; Other Information: PMCID: PMC4462980; PMID: 26229673; OAI: oai:pubmedcentral.nih.gov:4462980; Copyright (c) 2015 The Authors. Journal of Medical Radiation Sciences published by Wiley Publishing Asia Pty Ltd on behalf of Australian Institute of Radiography and New Zealand Institute of Medical Radiation Technology.; This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
Australia
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 62 RADIOLOGY AND NUCLEAR MEDICINE; ANALOG-TO-DIGITAL CONVERTERS; DATA ANALYSIS; DIFFUSION; GENES; GLIOMAS; METHYLATION; PATIENTS; PROBES; REDUCTION; VARIATIONS